decision tree

A decision tree represents complex rules as a series of simple conditions with sub-trees (branches) for further conditions depending on the outcome to the inital condition. Decision trees can be hand crafted (e.g. decision trees in IVR), but most commonly encountered in AI as the output of machine learning algorithms such as Quinlan's ID3 or C4.5, or as part of a random forest.